• Journal of Advanced Navigation Technology
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• v.19 no.4
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• pp.265-277
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• 2015

Automatic dependent surveillance-broadcast (ADS-B) is the core technology of communication, navigation and surveillance/air traffic management (CNS/ATM), automatically broadcasts its own position information using GNSS and has an advantage of lower geological constraints and faster update speed compared with legacy radar systems. EUROCONTROL defined all purpose structured eurocontrol surveillance information exchange (ASTERIX) CAT.021. ASTERIX CAT.021 is modified several times, but it has compatibility issues with previous version of it. In this paper, we have designed an efficient message processing module regardless of the version of ASTERIX CAT.021. This implemented module generates patterns to collect messages received from the network, after that, received messages are processed in the routine that is defined in accordance with the patterns.

• Journal of Fashion Business
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• v.8 no.1
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• pp.34-48
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• 2004

The purpose of this study is to explore emotion aspects of consumers purchasing clothing through cable television home shopping. Qualitative research method is used to widely understand how emotion aspects of consumers have effected on their purchasing behavior. The results of depth interviews may be classified into 13 feelings factors satisfaction, pleasure/delight, respect, attraction, fresh, convenience, unburdened, emptiness, displeasure/temper, anxiety, tedious, distrust, regret. The content of information acquiring from the process of clothing purchase decision making is analysed. In the problem recognition stage, purchase motivation were physical space (around people) and imaginary space(by how clothing goods are introduced to consumers thorough TV monitor). In the information search stage, purchasing action patterns to search information were situational pattern and habitual pattern. In alternative evaluation stage, the considering best important factors to choice clothes were quality, price, design, and color. In purchase stage, consumers said they felt anxiety, because of characteristics of purchase way that they should pay first and then received the ordered goods a fews days later. In post-purchase behavior stage, if consumers satisfied goods purchased through TV home shopping, they recommended it to around others, but unsatisfied with ordered goods, they tried to refund, exchange with anther one, or write it on homepage of the home shopping company.

• Journal of Information Technology Services
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• v.19 no.4
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• pp.49-61
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• 2020

Prior studies on technology predictions attempted to predict the emergence and spread of emerging technologies through the analysis of correlations and changes between data using objective data such as patents and research papers. Most of the previous studies predicted future technologies only from the viewpoint of technology development. Therefore, this study intends to conduct technical forecasting from the perspective of the consumer by using keyword search frequency of search portals such as NAVER before and after the introduction of emerging technologies. In this study, we analyzed healthcare technologies into three types : measurement technology, platform technology, and remote service technology. And for the keyword analysis on the healthcare, we converted the classification of technology perspective into the keyword classification of consumer perspective. (Blood pressure and blood sugar, healthcare diagnosis, appointment and prescription, and remote diagnosis and prescription) Naver Trend is used to analyze keyword trends from a consumer perspective. We also used the ARIMA model as a technology prediction model. Analyzing the search frequency (Naver trend) over 44 months, the final ARIMA models that can predict three types of healthcare technology keyword trends were estimated as "ARIMA (1,2,1) (1,0,0)", "ARIMA (0,1,0) (1,0,0)", "ARIMA (1,1,0) (0,0,0)". In addition, it was confirmed that the values predicted by the time series prediction model and the actual values for 44 months were moving in almost similar patterns in all intervals. Therefore, we can confirm that this time series prediction model for healthcare technology is very suitable.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2001.08a
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• pp.139-149
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• 2001

Since 1990, the National Cancer Institute(NCI) has screened more than 60.000 compounds against a panel of 60 human cancer cell lines. The 50-percent growth-inhibitory concentration (GI$_{50}$) values encode unexpectedly rich, detailed information on mechanisms of drug action and drug resistance. Each compound's pattern is like a fingerprint, essentially unique among the many billions of distinguishable possibilities. These activity patterns are being used in conjunction with molecular structural features of the tested agents to explore the NCI's database of more than 460, 000 compounds, and they are providing insight into potential target molecules and modulators of activity in the 60 cell lines. For example, the information is being used to search for candidate anticancer drugs that are not dependent on intact p53 suppressor gene function for their activity. It remains to be seen how effective this information-intensive strategy will be at generating new clinically active agents.s.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.9
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• pp.387-398
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• 2023

The COVID-19 outbreak has significantly impacted human lifestyles and patterns. It was recommended to avoid face-to-face contact and over-crowded indoor places as much as possible as COVID-19 spreads through air, as well as through droplets or aerosols. Therefore, if a person who has contacted a COVID-19 patient or was at the place where the COVID-19 patient occurred is concerned that he/she may have been infected with COVID-19, it can be fully expected that he/she will search for COVID-19 symptoms on Google. In this study, an exploratory data analysis using deep learning models(DNN & LSTM) was conducted to see if we could predict the number of confirmed COVID-19 cases by summoning Google Trends, which played a major role in surveillance and management of influenza, again and combining it with data on the number of confirmed COVID-19 cases. In particular, search term frequency data used in this study are available publicly and do not invade privacy. When the deep neural network model was applied, Seoul (9.6 million) with the largest population in South Korea and Busan (3.4 million) with the second largest population recorded lower error rates when forecasting including search term frequency data. These analysis results demonstrate that search term frequency data plays an important role in cities with a population above a certain size. We also hope that these predictions can be used as evidentiary materials to decide policies, such as the deregulation or implementation of stronger preventive measures.

• Journal of Intelligence and Information Systems
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• v.7 no.1
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• pp.97-121
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• 2001

Until now, we have believed that one of advantages of cyber market is that it can virtually display and sell goods because it does not necessary maintain expensive physical shops and inventories. But, in a highly competitive environment, business model that does away with goods in stock must be modified. As we know in the case of AMAZON, leading companies already consider merchandise management as a critical success factor in their business model. That is, a solution to compete against one's competitors in a highly competitive environment is merchandise management as in the traditional retail market. Cyber market has not only past sales data but also web log data before sales data that contains information of path that customer search and purchase on cyber market as compared with traditional retail market. So if we can correctly analyze the characteristics of before sales patterns using web log data, we can better prepare for the potential customers and effectively manage inventories and merchandises. We introduce a systematic analysis method to extract useful data for merchandise management - demand forecasting, evaluating & selecting - using web mining that is the application of data mining techniques to the World Wide Web. We use various techniques of web mining such as clustering, mining association rules, mining sequential patterns.

• Journal of the Korea Society of Computer and Information
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• v.7 no.3
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• pp.149-157
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• 2002

Todays, electronic commerce(EC) results to the revolution and new paradigm of business, more and more Web-based EC applications have emerged. But, it's web systems should be satisfied by customers and it should be successful to buying some goods in virtual stores with easy to use. The usability and acceptance of the EC web system is one of the key factors in the successful construction of EC system. In this paper, we considered the characteristics of information search and decision making process in the design of EC web system to be used easily and to be more acceptable to customers. On the basis of these characteristics, we could classified with the activities of the process of buying in the domestic web systems. And, the log files of experimental tasks were analyzed by the statistical method of data mining. As the these results, the important factors of the process of buying could be summarized, 5 user groups could be seen in EC customers, and the usage patterns of these groups were described. These results could be very useful to design user-oriented EC web system.

• Journal of KIISE:Databases
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• v.27 no.2
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• pp.216-226
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• 2000

This paper suggests a new access path, hashed B-tree which is an efficient access method for integrity checking. Hashed B-tree is based on the observation that most query patterns in enforcing integrity constraints are point queries. Hashed B-tree compresses the key by hashing procedure, which reduces the height of tree and results in fast node search. This method has the advantages such as it can be implemented easily and use the B-tree concurrency control and recovery algorithm with minor modifications.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.31A no.2
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• pp.94-103
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• 1994

In testing for practical scan disigned logic circuits, there may exist logic value constraints on some part of primary inputs due to various requirements on design and test. This paper presents a logic value system called taboo logic values which targets the test pattern generation of logic circuits under logic value constraints. The taboo logic system represents the logic value constraints and identifies additional logic value constraints through the implication of the tqaboo logic values using a taboo logic calculus. Those identified logic value constraints will guide the search during the test pattern generation of avoid the unfruitful searches and to identify redundant faults due to the logic value constraints very quickly. Finally, experimental results on ISCAS85 benchmark circuits will demonstrate the efficiency of the taboo logic values.

• Journal of the Korean Operations Research and Management Science Society
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• v.29 no.1
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• pp.17-30
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• 2004

There seems to be a renewed interest in Interorganizational relationship to search for strategic information partnerships. It is particularly noteworthy that no study has yet reported conflgurations at the level of interorganizational relationships nor compared such configurations across different types of ISO(interorganizational system). This paper seeks to uncover dominant configurations of interorganizational relationships across the various types of ISO. We Integrate relevant theoretical concepts from transaction cost economics, organization theory and political economy to develop a conceptual model of interorganizational relationships. We empirically uncover a set of hypothesis toward the patterns of interorganizetional relationships. Moreover the implications for further research pertaining to the logic and development of configurations were proposed.